A Discrete Hemodynamic Control Framework: Proof-of-Concept Study for Autonomous Drug Therapy in Acute Heart Failure.

OBJECTIVES

Managing acute heart failure (AHF) involves the dual challenges of stabilizing hemodynamics while minimizing myocardial oxygen consumption. This is a clinically significant and technically challenging issue due to complex cardiovascular interactions and trade-offs between therapeutic goals. We aim to develop a discrete hemodynamic control framework for autonomous drug therapy that enhances both control versatility and clinical potential.

METHODS

A comprehensive multi-input, multi-output model was derived to capture causal relationships linking drug infusion, cardiovascular parameters, and hemodynamic responses. Based on this model, we designed an optimal control framework capable of regulating arbitrary hemodynamic targets (e.g., arterial pressure, cardiac output, left atrial pressure, right atrial pressure), minimizing myocardial oxygen consumption, accommodating multiple guideline-concordant drug classes, and enforcing clinical constraints such as dosage limits and contraindications. The discrete design enables compatibility with standard hemodynamic measurements in ICU/CCU settings. Control performance was validated using a cardiovascular simulator.

RESULTS

The system achieved multi-dimensional regulation of hemodynamics and reduced myocardial oxygen consumption across a range of AHF scenarios. It also identified pharmacologically untreatable cases by evaluating the reachable hemodynamic range. Performance remained stable despite inter-patient variability in drug sensitivities, circulatory properties, and baroreflex activity.

CONCLUSIONS

The proposed system may function as a physician-assistive tool and a foundation for autonomous drug therapy in AHF.

SIGNIFICANCES: By integrating physiologically grounded modeling with practical clinical constraints, the system offers a novel and scalable approach to optimize drug therapy in AHF. It has the potential to improve treatment precision, reduce clinician burden, and advance next-generation critical care.